Integrative genomics identifies a convergent molecular subtype that links epigenomic with transcriptomic differences in autism

Genome-wide identification and analysis of recurring patterns of epigenetic variation across individuals

Epigenetic mapping studies across individuals have identified many positions of epigenetic variation across the human genome. However the relationships between these positions, and in particular global patterns that recur in many regions of the genome, remains understudied. In this study, we use a stacked chromatin state model to systematically learn global patterns of epigenetic variation across individuals and annotate the human genome based on them. We apply this framework to histone modification data across individuals in lymphoblastoid cell lines and across autism spectrum disorder cases and controls in prefrontal cortex tissue. We find that global patterns are correlated across multiple histone modifications and with gene expression. We use the global patterns as a framework to predict trans-regulators and study a complex disorder. The frameworks for identifying and analyzing global patterns of epigenetic variation are general and we expect will be useful in other systems.

Cognitive and Synaptic Impairment Induced by Deficiency of Autism Risk Gene Smarcc2 and its Rescue by Histone Deacetylase Inhibition

SMARCC2 , which encodes BAF170, a core subunit of chromatin remodeling BAF complex, is one of the top-ranking risk genes for autism spectrum disorder (ASD). However, the mechanisms linking SMARCC2 haploinsufficiency to ASD remain poorly understood. Genome-wide RNA-seq analysis revealed that SMARCC2 was significantly diminished in iPSC-derived neurons from idiopathic ASD patients. ChIP-seq of SMARCC2 demonstrated its binding to many other ASD risk genes involved in transcriptional regulation. Smarcc2 deficiency in prefrontal cortex (PFC) of adolescent mice led to impaired working memory, with largely intact social and anxiety-like behaviors. Significant downregulation of genes enriched in synaptic transmission were found in PFC of S marcc2 -deficient mice by RNA-seq and qPCR profiling. In parallel, electrophysiological recordings uncovered the significant impairment of GABAergic and glutamatergic synaptic currents in S marcc2 -deficient PFC pyramidal neurons. Smarcc2 bound to HDAC2, and Smarcc2 deficiency led to the reduced global histone acetylation and H3K9ac enrichment at synaptic gene Slc1a3 (EAAT1), Slc6a1 (GAT1), and Slc32a1 (VGAT) promoters. Treatment of S marcc2 -deficient mice with romidepsin, a class I HDAC inhibitor, restored histone acetylation, working memory and some synaptic gene expression. These findings highlight the critical role of Smarcc2 in regulating cognitive and synaptic function, suggesting that targeting HDAC could alleviate deficits in Smarcc2-associated neurodevelopmental disorders.

CHAS infers cell type-specific signatures in bulk brain histone acetylation studies of neurological and psychiatric disorders

Epigenomic profiling of the brain has largely been done on bulk tissues, limiting our understanding of cell type-specific epigenetic changes in disease states. Here, we introduce cell type-specific histone acetylation score (CHAS), a computational tool for inferring cell type-specific signatures in bulk brain H3K27ac profiles. We applied CHAS to >300 H3K27ac chromatin immunoprecipitation sequencing samples from studies of Alzheimer's disease, Parkinson's disease, autism spectrum disorder, schizophrenia, and bipolar disorder in bulk postmortem brain tissue. In addition to recapitulating known disease-associated shifts in cellular proportions, we identified cell type-specific biological insights into brain-disorder-associated regulatory variation. In most cases, genetic risk and epigenetic dysregulation targeted different cell types, suggesting independent mechanisms. For instance, genetic risk of Alzheimer's disease was exclusively enriched within microglia, while epigenetic dysregulation predominantly fell within oligodendrocyte-specific H3K27ac regions. In addition, reanalysis of the original datasets using CHAS enabled identification of biological pathways associated with each neurological and psychiatric disorder at cellular resolution.

Bioinformatic Analysis of Autism-Related miRNAs and Their PoTential as Biomarkers for Autism Epigenetic Inheritance

BACKGROUND/OBJECTIVES

The dysregulation of miRNA expression in samples from autistic individuals indicates that they are involved in autism. The participation of miRNAs in paternal epigenetic inheritance has also been reported. This study used bioinformatics tools to analyze the literature and genetic databases to search for miRNAs associated with autism, aiming to explore their suitability to investigate paternal epigenetic inheritance.

METHODS

Autism-related miRNAs were searched in public databases using bioinformatic tools (miRNA-to-genes analysis). The genes targeted by these autism-related miRNAs, which are common to neurons, sperm, and PBMCs, were identified. Enrichment analyses were performed to identify the biological processes regulated by the candidate miRNAs. Autism-related miRNAs were also identified by an inverse analysis (genes-to-miRNA analysis), starting from autism-related genes.

RESULTS

In the miRNA-to-gene analysis, 416 miRNAs involved in autism were found, of which 77 were expressed in sperm, PBMCs, and neurons. From these, 18 were differentially expressed in the brain and in at least one peripheral sample (saliva or blood), suggesting that they might be suitable to be used in the investigation of autism biomarkers and inheritance. In the genes-to-miRNA analysis, 36 miRNAs were identified, from which 9 coincided with the results of direct analysis.

CONCLUSIONS

Although there is no consensus about miRNAs related to autism, there are candidate miRNAs that show clear potential to be explored as biomarkers. The coincidence in the expression of miRNAs in sperm, neurons, and PBMCs indicates that they are valuable biological samples to study the role of miRNAs in the paternal epigenetic inheritance of autism.

Autism-Associated Genes and Neighboring lncRNAs Converge on Key Gene Regulatory Networks

The diversity of genes implicated in autism spectrum disorder (ASD) creates challenges for identifying core pathophysiological mechanisms. Aggregation of seven different classes of genetic variants implicated in ASD, in a database we call Consensus-ASD, reveals shared features across distinct types of ASD variants. Functional interrogation of 19 ASD genes and 9 neighboring long non-coding RNAs (lncRNAs) using CRISPR-Cas13 strikingly revealed differential gene expression profiles that were significantly enriched for other ASD genes. Furthermore, construction of a gene regulatory network (GRN) enabled the identification of central regulators that exhibit convergently altered activity upon ASD gene disruption. Thus, this study reveals how perturbing distinct ASD-associated genes can lead to shared, broad dysregulation of GRNs with critical relevance to ASD. This provides a crucial framework for understanding how diverse genes, including lncRNAs, can play convergent roles in key neurodevelopmental processes and ultimately contribute to ASD.

Transcriptomic Evidence Reveals the Dysfunctional Mechanism of Synaptic Plasticity Control in ASD

BACKGROUND/OBJECTIVES

A prominent endophenotype in Autism Spectrum Disorder (ASD) is the synaptic plasticity dysfunction, yet the molecular mechanism remains elusive. As a prototype, we investigate the postsynaptic signal transduction network in glutamatergic neurons and integrate single-cell nucleus transcriptomics data from the Prefrontal Cortex (PFC) to unveil the malfunction of translation control.

METHODS

We devise an innovative and highly dependable pipeline to transform our acquired signal transduction network into an mRNA Signaling-Regulatory Network (mSiReN) and analyze it at the RNA level. We employ Cell-Specific Network Inference via Integer Value Programming and Causal Reasoning (CS-NIVaCaR) to identify core modules and Cell-Specific Probabilistic Contextualization for mRNA Regulatory Networks (CS-ProComReN) to quantitatively reveal activated sub-pathways involving MAPK1, MKNK1, RPS6KA5, and MTOR across different cell types in ASD.

RESULTS

The results indicate that specific pivotal molecules, such as EIF4EBP1 and EIF4E, lacking Differential Expression (DE) characteristics and responsible for protein translation with long-term potentiation (LTP) or long-term depression (LTD), are dysregulated. We further uncover distinct activation patterns causally linked to the EIF4EBP1-EIF4E module in excitatory and inhibitory neurons.

CONCLUSIONS

Importantly, our work introduces a methodology for leveraging extensive transcriptomics data to parse the signal transduction network, transforming it into mSiReN, and mapping it back to the protein level. These algorithms can serve as potent tools in systems biology to analyze other omics and regulatory networks. Furthermore, the biomarkers within the activated sub-pathways, revealed by identifying convergent dysregulation, illuminate potential diagnostic and prognostic factors in ASD.

MYT1L deficiency impairs excitatory neuron trajectory during cortical development

Mutations reducing the function of MYT1L, a neuron-specific transcription factor, are associated with a syndromic neurodevelopmental disorder. MYT1L is used as a pro-neural factor in fibroblast-to-neuron transdifferentiation and is hypothesized to influence neuronal specification and maturation, but it is not clear which neuron types are most impacted by MYT1L loss. In this study, we profile 412,132 nuclei from the forebrains of wild-type and MYT1L-deficient mice at three developmental stages: E14 at the peak of neurogenesis, P1 when cortical neurons have been born, and P21 when neurons are maturing, to examine the role of MYT1L levels on neuronal development. MYT1L deficiency disrupts cortical neuron proportions and gene expression, primarily affecting neuronal maturation programs. Effects are mostly cell autonomous and persistent through development. While MYT1L can both activate and repress gene expression, the repressive effects are most sensitive to haploinsufficiency, likely mediating MYT1L syndrome. These findings illuminate MYT1L's role in orchestrating gene expression during neuronal development, providing insights into the molecular underpinnings of MYT1L syndrome.

Targeting epigenetic dysregulation in autism spectrum disorders

Autism spectrum disorders (ASD) comprise a range of neurodevelopmental pathologies characterized by deficits in social interaction and repetitive behaviors, collectively affecting almost 1% of the worldwide population. Deciphering the etiology of ASD has proven challenging due to the intricate interplay of genetic and environmental factors and the variety of molecular pathways affected. Epigenomic alterations have emerged as key players in ASD etiology. Their research has led to the identification of biomarkers for diagnosis and pinpointed specific gene targets for therapeutic interventions. This review examines the role of epigenetic alterations, resulting from both genetic and environmental influences, as a central causative factor in ASD, delving into its contribution to pathogenesis and treatment strategies.

The neuroscience of mental illness: Building toward the future

Mental illnesses arise from dysfunction in the brain. Although numerous extraneural factors influence these illnesses, ultimately, it is the science of the brain that will lead to novel therapies. Meanwhile, our understanding of this complex organ is incomplete, leading to the oft-repeated trope that neuroscience has yet to make significant contributions to the care of individuals with mental illnesses. This review seeks to counter this narrative, using specific examples of how neuroscientific advances have contributed to progress in mental health care in the past and how current achievements set the stage for further progress in the future.

Dynamic convergence of autism disorder risk genes across neurodevelopment

Over a hundred risk genes underlie risk for autism spectrum disorder (ASD) but the extent to which they converge on shared downstream targets to increase ASD risk is unknown. To test the hypothesis that cellular context impacts the nature of convergence, here we apply a pooled CRISPR approach to target 29 ASD loss-of-function genes in human induced pluripotent stem cell (hiPSC)-derived neural progenitor cells, glutamatergic neurons, and GABAergic neurons. Two distinct approaches (gene-level and network-level analyses) demonstrate that convergence is greatest in mature glutamatergic neurons. Convergent effects are dynamic, varying in strength, composition, and biological role between cell types, increasing with functional similarity of the ASD genes examined, and driven by cell-type-specific gene co-expression patterns. Stratification of ASD genes yield targeted drug predictions capable of reversing gene-specific convergent signatures in human cells and ASD-related behaviors in zebrafish. Altogether, convergent networks downstream of ASD risk genes represent novel points of individualized therapeutic intervention.

A clustering approach identifies an Autism Spectrum Disorder subtype more responsive to chronic oxytocin treatment

Over the last decade, a number of clinical trials have reported effects of chronic treatment with intranasal oxytocin on autistic symptoms but with inconsistent findings. Autism is a heterogeneous disorder and one factor which may influence treatment outcome is whether a subtype of individuals is more sensitive to oxytocin. In a recent cross-over trial on 41 young autistic children we reported that 44% showed a reliable improvement in clinical symptoms (Autism Diagnostic Observation Schedule, ADOS-2) after a placebo-controlled, 6-week intranasal oxytocin intervention where treatment was given every other day followed by a period of positive social interaction. In the current re-assessment of the data, we used an unsupervised data-driven cluster analysis approach to identify autism subtypes using 23 different demographic, social subtype, endocrine, eye-tracking and clinical symptom measures taken before treatment and this revealed an optimum of two different subtypes. We then assessed the proportion of identified responders to oxytocin and found that while 61.5% of one subtype included responders only 13.3% of the other did so. During the placebo phase there was no difference between the two subtypes for the small proportion of responders (19.2% vs 6.7%). This oxytocin-sensitive subtype also showed overall significant post-treatment clinical and eye-tracking measure changes. The oxytocin-sensitive subtype was primarily characterized at baseline by lower initial clinical severity (ADOS-2) and greater interest in the eye-region of emotional faces. These features alone were nearly as efficient in identifying the two subtypes as all 23 baseline measures and this easy-to-conduct approach may help rapidly and objectively screen for oxytocin responders. Future clinical trials using oxytocin interventions may therefore achieve greater success by focusing on children with this specific autism subtype and help develop individualized oxytocin intervention.

Targeted co-expression networks for the study of traits

Weighted Gene Co-expression Network Analysis (WGCNA) is a widely used approach for the generation of gene co-expression networks. However, networks generated with this tool usually create large modules with a large set of functional annotations hard to decipher. We have developed TGCN, a new method to create Targeted Gene Co-expression Networks. This method identifies the transcripts that best predict the trait of interest based on gene expression using a refinement of the LASSO regression. Then, it builds the co-expression modules around those transcripts. Algorithm properties were characterized using the expression of 13 brain regions from the Genotype-Tissue Expression project. When comparing our method with WGCNA, TGCN networks lead to more precise modules that have more specific and yet rich biological meaning. Then, we illustrate its applicability by creating an APP-TGCN on The Religious Orders Study and Memory and Aging Project dataset, aiming to identify the molecular pathways specifically associated with APP role in Alzheimer's disease. Main biological findings were further validated in two independent cohorts. In conclusion, we provide a new framework that serves to create targeted networks that are smaller, biologically relevant and useful in high throughput hypothesis driven research. The TGCN R package is available on Github: https://github.com/aliciagp/TGCN .

Towards understanding sex differences in autism spectrum disorders

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by social deficits, repetitive behaviours and lack of empathy. Its significant genetic heritability and potential comorbidities often lead to diagnostic and therapeutic challenges. This review addresses the biological basis of ASD, focusing on the sex differences in gene expression and hormonal influences. ASD is more commonly diagnosed in males at a ratio of 4:1, indicating a potential oversight in female-specific ASD research and a risk of underdiagnosis in females. We consider how ASD manifests differently across sexes by exploring differential gene expression in female and male brains and consider how variations in steroid hormones influence ASD characteristics. Synaptic function, including excitation/inhibition ratio imbalance, is influenced by gene mutations and this is explored as a key factor in the cognitive and behavioural manifestations of ASD. We also discuss the role of micro RNAs (miRNAs) and highlight a novel mutation in miRNA-873, which affects a suite of key synaptic genes, neurexin, neuroligin, SHANK and post-synaptic density proteins, implicated in the pathology of ASD. Our review suggests that genetic predisposition, sex differences in brain gene expression, and hormonal factors significantly contribute to the presentation, identification and severity of ASD, necessitating sex-specific considerations in diagnosis and treatments. These findings advocate for personalized interventions to improve the outcomes for individuals with ASD.

Relationship between sex biases in gene expression and sex biases in autism and Alzheimer's disease

BACKGROUND

Sex differences in the brain may play an important role in sex-differential prevalence of neuropsychiatric conditions.

METHODS

In order to understand the transcriptional basis of sex differences, we analyzed multiple, large-scale, human postmortem brain RNA-Seq datasets using both within-region and pan-regional frameworks.

RESULTS

We find evidence of sex-biased transcription in many autosomal genes, some of which provide evidence for pathways and cell population differences between chromosomally male and female individuals. These analyses also highlight regional differences in the extent of sex-differential gene expression. We observe an increase in specific neuronal transcripts in male brains and an increase in immune and glial function-related transcripts in female brains. Integration with single-nucleus data suggests this corresponds to sex differences in cellular states rather than cell abundance. Integration with case-control gene expression studies suggests a female molecular predisposition towards Alzheimer's disease, a female-biased disease. Autism, a male-biased diagnosis, does not exhibit a male predisposition pattern in our analysis.

CONCLUSION

Overall, these analyses highlight mechanisms by which sex differences may interact with sex-biased conditions in the brain. Furthermore, we provide region-specific analyses of sex differences in brain gene expression to enable additional studies at the interface of gene expression and diagnostic differences.

Molecular cascades and cell type-specific signatures in ASD revealed by single-cell genomics

Genomic profiling in postmortem brain from autistic individuals has consistently revealed convergent molecular changes. What drives these changes and how they relate to genetic susceptibility in this complex condition are not well understood. We performed deep single-nucleus RNA sequencing (snRNA-seq) to examine cell composition and transcriptomics, identifying dysregulation of cell type-specific gene regulatory networks (GRNs) in autism spectrum disorder (ASD), which we corroborated using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) and spatial transcriptomics. Transcriptomic changes were primarily cell type specific, involving multiple cell types, most prominently interhemispheric and callosal-projecting neurons, interneurons within superficial laminae, and distinct glial reactive states involving oligodendrocytes, microglia, and astrocytes. Autism-associated GRN drivers and their targets were enriched in rare and common genetic risk variants, connecting autism genetic susceptibility and cellular and circuit alterations in the human brain.

MYT1L deficiency impairs excitatory neuron trajectory during cortical development

Mutations that reduce the function of MYT1L, a neuron-specific transcription factor, are associated with a syndromic neurodevelopmental disorder. Furthermore, MYT1L is routinely used as a proneural factor in fibroblast-to-neuron transdifferentiation. MYT1L has been hypothesized to play a role in the trajectory of neuronal specification and subtype specific maturation, but this hypothesis has not been directly tested, nor is it clear which neuron types are most impacted by MYT1L loss. In this study, we profiled 313,335 nuclei from the forebrains of wild-type and MYT1L-deficient mice at two developmental stages: E14 at the peak of neurogenesis and P21, when neurogenesis is complete, to examine the role of MYT1L levels in the trajectory of neuronal development. We found that MYT1L deficiency significantly disrupted the relative proportion of cortical excitatory neurons at E14 and P21. Significant changes in gene expression were largely concentrated in excitatory neurons, suggesting that transcriptional effects of MYT1L deficiency are largely due to disruption of neuronal maturation programs. Most effects on gene expression were cell autonomous and persistent through development. In addition, while MYT1L can both activate and repress gene expression, the repressive effects were most sensitive to haploinsufficiency, and thus more likely mediate MYT1L syndrome. These findings illuminate the intricate role of MYT1L in orchestrating gene expression dynamics during neuronal development, providing insights into the molecular underpinnings of MYT1L syndrome.

Neuroimmune mechanisms in autism etiology - untangling a complex problem using human cellular models

Autism spectrum disorder (ASD) affects 1 in 36 people and is more often diagnosed in males than in females. Core features of ASD are impaired social interactions, repetitive behaviors and deficits in verbal communication. ASD is a highly heterogeneous and heritable disorder, yet its underlying genetic causes account only for up to 80% of the cases. Hence, a subset of ASD cases could be influenced by environmental risk factors. Maternal immune activation (MIA) is a response to inflammation during pregnancy, which can lead to increased inflammatory signals to the fetus. Inflammatory signals can cross the placenta and blood brain barriers affecting fetal brain development. Epidemiological and animal studies suggest that MIA could contribute to ASD etiology. However, human mechanistic studies have been hindered by a lack of experimental systems that could replicate the impact of MIA during fetal development. Therefore, mechanisms altered by inflammation during human pre-natal brain development, and that could underlie ASD pathogenesis have been largely understudied. The advent of human cellular models with induced pluripotent stem cell (iPSC) and organoid technology is closing this gap in knowledge by providing both access to molecular manipulations and culturing capability of tissue that would be otherwise inaccessible. We present an overview of multiple levels of evidence from clinical, epidemiological, and cellular studies that provide a potential link between higher ASD risk and inflammation. More importantly, we discuss how stem cell-derived models may constitute an ideal experimental system to mechanistically interrogate the effect of inflammation during the early stages of brain development.

Relationship between sex biases in gene expression and sex biases in autism and Alzheimer's disease

Sex differences in the brain may play an important role in sex-differential prevalence of neuropsychiatric conditions. In order to understand the transcriptional basis of sex differences, we analyzed multiple, large-scale, human postmortem brain RNA-seq datasets using both within-region and pan-regional frameworks. We find evidence of sex-biased transcription in many autosomal genes, some of which provide evidence for pathways and cell population differences between chromosomally male and female individuals. These analyses also highlight regional differences in the extent of sex-differential gene expression. We observe an increase in specific neuronal transcripts in male brains and an increase in immune and glial function-related transcripts in female brains. Integration with single-cell data suggests this corresponds to sex differences in cellular states rather than cell abundance. Integration with case-control gene expression studies suggests a female molecular predisposition towards Alzheimer's disease, a female-biased disease. Autism, a male-biased diagnosis, does not exhibit a male predisposition pattern in our analysis. Finally, we provide region specific analyses of sex differences in brain gene expression to enable additional studies at the interface of gene expression and diagnostic differences.

Methyl-CpG binding domain 2 (Mbd2) is an epigenetic regulator of autism-risk genes and cognition

The Methyl-CpG-Binding Domain Protein family has been implicated in neurodevelopmental disorders. The Methyl-CpG-binding domain 2 (Mbd2) binds methylated DNA and was shown to play an important role in cancer and immunity. Some evidence linked this protein to neurodevelopment. However, its exact role in neurodevelopment and brain function is mostly unknown. Here we show that Mbd2-deficiency in mice (Mbd2-/-) results in deficits in cognitive, social and emotional functions. Mbd2 binds regulatory DNA regions of neuronal genes in the hippocampus and loss of Mbd2 alters the expression of hundreds of genes with a robust down-regulation of neuronal gene pathways. Further, a genome-wide DNA methylation analysis found an altered DNA methylation pattern in regulatory DNA regions of neuronal genes in Mbd2-/- mice. Differentially expressed genes significantly overlap with gene-expression changes observed in brains of Autism Spectrum Disorder (ASD) individuals. Notably, downregulated genes are significantly enriched for human ortholog ASD risk genes. Observed hippocampal morphological abnormalities were similar to those found in individuals with ASD and ASD rodent models. Hippocampal Mbd2 knockdown partially recapitulates the behavioral phenotypes observed in Mbd2-/- mice. These findings suggest that Mbd2 is a novel epigenetic regulator of genes that are associated with ASD in humans. Mbd2 loss causes behavioral alterations that resemble those found in ASD individuals.

Mouse nerve growth factor suppresses neuronal apoptosis in valproic acid-induced autism spectrum disorder rats by regulating the phosphoinositide-3-kinase/serine/threonine kinase signaling pathway

BACKGROUND

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by deficits in social communication and restrictive behaviors. Mouse nerve growth factor (mNGF), a neurotrophic factor, is critical for neuronal growth and survival, and the mNGF treatment is considered a promising therapy for neurodegeneration. In light of this, we aimed to evaluate the effect of mNGF on neurological function in ASD.

METHODS

An ASD rat model was established by intraperitoneal injection of valproic acid (VPA). Social behavior, learning, and memory of the rats were measured. TdT-mediated dUTP Nick-end labeling and Nissl assays were performed to detect neuronal apoptosis and survival in the hippocampus and prefrontal cortex. Apoptosis-related proteins and oxidative stress markers were detected.

RESULTS

mNGF improved locomotor activity, exploratory behavior, social interaction, and spatial learning and memory in VPA-induced ASD rats. In the hippocampus and prefrontal cortex, mNGF suppressed neuronal apoptosis, increased the number of neurons, superoxide dismutase, and glutathione levels, and decreased reactive oxygen species, nitric oxide, TNF-α, and IL-1β levels compared with the VPA group. In addition, mNGF increased the levels of Bcl-2, p-phosphoinositide-3-kinase (PI3K), and p-serine/threonine kinase (Akt), and decreased the levels of Bax and cleaved caspase-3, while the PI3K inhibitor LY294002 reversed these effects.

CONCLUSION

These data suggest that mNGF suppressed neuronal apoptosis and ameliorated the abnormal behaviors in VPA-induced ASD rats, in part, by activating the PI3K/Akt signaling pathway.

Autistic spectrum disorder (ASD) - Gene, molecular and pathway signatures linking systemic inflammation, mitochondrial dysfunction, transsynaptic signalling, and neurodevelopment

Background

Despite advances in autism spectrum disorder (ASD) research and the vast genomic, transcriptomic, and proteomic data available, there are still controversies regarding the pathways and molecular signatures underlying the neurodevelopmental disorders leading to ASD.

Purpose

To delineate these underpinning signatures, we examined the two largest gene expression meta-analysis datasets obtained from the brain and peripheral blood mononuclear cells (PBMCs) of 1355 ASD patients and 1110 controls.

Methods

We performed network, enrichment, and annotation analyses using the differentially expressed genes, transcripts, and proteins identified in ASD patients.

Results

Transcription factor network analyses in up- and down-regulated genes in brain tissue and PBMCs in ASD showed eight main transcription factors, namely: BCL3, CEBPB, IRF1, IRF8, KAT2A, NELFE, RELA, and TRIM28. The upregulated gene networks in PBMCs of ASD patients are strongly associated with activated immune-inflammatory pathways, including interferon-α signaling, and cellular responses to DNA repair. Enrichment analyses of the upregulated CNS gene networks indicate involvement of immune-inflammatory pathways, cytokine production, Toll-Like Receptor signalling, with a major involvement of the PI3K-Akt pathway. Analyses of the downregulated CNS genes suggest electron transport chain dysfunctions at multiple levels. Network topological analyses revealed that the consequent aberrations in axonogenesis, neurogenesis, synaptic transmission, and regulation of transsynaptic signalling affect neurodevelopment with subsequent impairments in social behaviours and neurocognition. The results suggest a defense response against viral infection.

Conclusions

Peripheral activation of immune-inflammatory pathways, most likely induced by viral infections, may result in CNS neuroinflammation and mitochondrial dysfunction, leading to abnormalities in transsynaptic transmission, and brain neurodevelopment.

Shared and divergent contribution of vitamin A and oxytocin to the aetiology of autism spectrum disorder

Rare genetic variations contribute to the heterogeneity of autism spectrum disorder (ASD) and the responses to various interventions for ASD probands. However, the associated molecular underpinnings remain unclear. Herein, we estimated the association between rare genetic variations in 410 vitamin A (VA)-related genes (VARGs) and ASD aetiology using publicly available de novo mutations (DNMs), rare inherited variants, and copy number variations (CNVs) from about 50,000 ASD probands and 20,000 normal controls (discovery and validation cohorts). Additionally, given the functional relevance of VA and oxytocin, we systematically compared the similarities and differences between VA and oxytocin with respect to ASD aetiology and evaluated their potential for clinical applications. Functional DNMs and pathogenic CNVs in VARGs contributed to ASD pathogenesis in the discovery and validation cohorts. Additionally, 324 potential VA-related biomarkers were identified, 243 of which were shared with previously identified oxytocin-related biomarkers, while 81 were unique VA biomarkers. Moreover, multivariable logistic regression analysis revealed that both VA- and oxytocin-related biomarkers were able to predict ASD aetiology for individuals carrying functional DNM in corresponding biomarkers with an average precision of 0.94. As well as, convergent and divergent functions were also identified between VA- and oxytocin-related biomarkers. The findings of this study provide a basis for future studies aimed at understanding the pathophysiological mechanisms underlying ASD while also defining a set of potential molecular biomarkers for adjuvant diagnosis and intervention in ASD.

Characterization of Gene Regulatory Elements in Human Fetal Cortical Development: Enhancing Our Understanding of Neurodevelopmental Disorders and Evolution

The neocortex is the region that most distinguishes human brain from other mammals and primates [Annu Rev Genet. 2021 Nov;55(1):555-81]. Studying the development of human cortex is important in understanding the evolutionary changes occurring in humans relative to other primates, as well as in elucidating mechanisms underlying neurodevelopmental disorders. Cortical development is a highly regulated process, spatially and temporally coordinated by expression of essential transcriptional factors in response to signaling pathways [Neuron. 2019 Sep;103(6):980-1004]. Enhancers are the most well-understood cis-acting, non-protein-coding regulatory elements that regulate gene expression [Nat Rev Genet. 2014 Apr;15(4):272-86]. Importantly, given the conservation of both DNA sequence and molecular function of the majority of proteins across mammals [Genome Res. 2003 Dec;13(12):2507-18], enhancers [Science. 2015 Mar;347(6226):1155-9], which are far more divergent at the sequence level, likely account for the phenotypes that distinguish the human brain by changing the regulation of gene expression. In this review, we will revisit the conceptual framework of gene regulation during human brain development, as well as the evolution of technologies to study transcriptional regulation, with recent advances in genome biology that open a window allowing us to systematically characterize cis-regulatory elements in developing human brain [Hum Mol Genet. 2022 Oct;31(R1):R84-96]. We provide an update on work to characterize the suite of all enhancers in the developing human brain and the implications for understanding neuropsychiatric disorders. Finally, we discuss emerging therapeutic ideas that utilize our emerging knowledge of enhancer function.

Dysregulation of immune and metabolism pathways in maternal immune activation induces an increased risk of autism spectrum disorders

AIMS

Maternal immune activation (MIA) via infection during pregnancy is known to be an environmental risk factor for neurodevelopmental disorders and the development of autism spectrum disorders (ASD) in the offspring, but it still remains elusive that the molecular relevance between infection-induced abnormal neurodevelopmental events and an increased risk for ASD development.

MAIN METHODS

Fully considering the extremely high genetic heterogeneity of ASD and the universality of risk-gene with minimal effect-sizes, the gene and pathway-based association analysis was performed with the transcriptomic and DNA methylation landscapes of temporal human embryonic brain development and ASD, and the time-course transcriptional profiling of MIA. We conducted the transcriptional profiling of mouse abnormal neurodevelopment two days following induced MIA via LPS injection at E10.5.

KEY FINDINGS

A novel evidence was proved that illustrated altering four immune and metabolism-related risk pathways, including starch and sucrose metabolism, ribosome, protein processing in endoplasmic reticulum, and retrograde endocannabinoid signaling pathway, which were prominent involvement in the process of MIA regulating abnormal fetal brain development to induce an increased risk of ASD. Here, we have observed that almost all key genes within these risk pathways are significantly differentially expressed at embryonic days (E) 10.5-12.5, which is considered to be the optimal coincidence window of mouse embryonic brain development to study the intimate association between MIA and ASD using mouse animal models.

SIGNIFICANCE

There search establishes that MIA causes dysregulation of immune and metabolic pathways, which leads to abnormal embryonic neurodevelopment, thus promoting development of ASD symptoms in offspring.

Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings

Major depressive disorder (MDD) is a complex and heterogeneous psychiatric syndrome with genetic and environmental influences. In addition to neuroanatomical and circuit-level disturbances, dysregulation of the brain transcriptome is a key phenotypic signature of MDD. Postmortem brain gene expression data are uniquely valuable resources for identifying this signature and key genomic drivers in human depression; however, the scarcity of brain tissue limits our capacity to observe the dynamic transcriptional landscape of MDD. It is therefore crucial to explore and integrate depression and stress transcriptomic data from numerous, complementary perspectives to construct a richer understanding of the pathophysiology of depression. In this review, we discuss multiple approaches for exploring the brain transcriptome reflecting dynamic stages of MDD: predisposition, onset, and illness. We next highlight bioinformatic approaches for hypothesis-free, genome-wide analyses of genomic and transcriptomic data and their integration. Last, we summarize the findings of recent genetic and transcriptomic studies within this conceptual framework.

Single-nucleus gene and gene set expression-based similarity network fusion identifies autism molecular subtypes

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that is highly phenotypically and genetically heterogeneous. With the accumulation of biological sequencing data, more and more studies shift to molecular subtype-first approach, from identifying molecular subtypes based on genetic and molecular data to linking molecular subtypes with clinical manifestation, which can reduce heterogeneity before phenotypic profiling.

RESULTS

In this study, we perform similarity network fusion to integrate gene and gene set expression data of multiple human brain cell types for ASD molecular subtype identification. Then we apply subtype-specific differential gene and gene set expression analyses to study expression patterns specific to molecular subtypes in each cell type. To demonstrate the biological and practical significance, we analyze the molecular subtypes, investigate their correlation with ASD clinical phenotype, and construct ASD molecular subtype prediction models.

CONCLUSIONS

The identified molecular subtype-specific gene and gene set expression may be used to differentiate ASD molecular subtypes, facilitating the diagnosis and treatment of ASD. Our method provides an analytical pipeline for the identification of molecular subtypes and even disease subtypes of complex disorders.

Protein interaction studies in human induced neurons indicate convergent biology underlying autism spectrum disorders

Autism spectrum disorders (ASDs) have been linked to genes with enriched expression in the brain, but it is unclear how these genes converge into cell-type-specific networks. We built a protein-protein interaction network for 13 ASD-associated genes in human excitatory neurons derived from induced pluripotent stem cells (iPSCs). The network contains newly reported interactions and is enriched for genetic and transcriptional perturbations observed in individuals with ASDs. We leveraged the network data to show that the ASD-linked brain-specific isoform of ANK2 is important for its interactions with synaptic proteins and to characterize a PTEN-AKAP8L interaction that influences neuronal growth. The IGF2BP1-3 complex emerged as a convergent point in the network that may regulate a transcriptional circuit of ASD-associated genes. Our findings showcase cell-type-specific interactomes as a framework to complement genetic and transcriptomic data and illustrate how both individual and convergent interactions can lead to biological insights into ASDs.

Translating precision medicine for autism spectrum disorder: A pressing need

Autism spectrum disorder (ASD) is a heterogenous group of neurodevelopmental disorders (NDDs) with a high unmet medical need. Currently, ASD is diagnosed according to behavior-based criteria that overlook clinical and genomic heterogeneity, thus repeatedly resulting in failed clinical trials. Here, we summarize the scientific evidence pointing to the pressing need to create a precision medicine framework for ASD and other NDDs. We discuss the role of omics and systems biology to characterize more homogeneous disease subtypes with different underlying pathophysiological mechanisms and to determine corresponding tailored treatments. Finally, we provide recent initiatives towards tackling the complexity in NDDs for precision medicine and cost-effective drug discovery.

Effects of different doses of lithium on the central nervous system in the rat valproic acid model of autism

Epidemiological studies have shown that low doses of lithium in the environment can have beneficial effects on mental health. Autism spectrum disorder, a neurodevelopmental disorder in which patients exhibit abnormal behaviors, pharmacological interventions usually relied on a range of psychotropic medications. However, such medications often produce severe side effects or are ineffective in symptoms. Finding alternative ways to improve abnormal behaviors in individuals with autism are warranted, in which case lithium may be a relatively safe and effective medication. Lithium salt therapy is used to treat a variety of neuropsychiatric disorders and has neuroprotective effects. In this study, we investigated the effects of different doses of lithium on neurobehavioural disorders using the rat model of autism established by valproic acid (VPA) injection. Lithium was observed to have an ameliorative effect on the social cognitive, social memory and anxiety levels in the rat model of autism. Immunofluorescence staining showed that subchronic LiCl administration (1.0 mmol/kg) significantly reduced the number of Iba-1 positive cells in the CA1 region of the hippocampus in VPA group and brought it close to the levels of control group. Significantly lower levels of the pro-inflammatory marker IL-6 were observed in the hippocampus and serum after lithium treatment. In addition, the lithium treatment increased the levels of H3K9 acetylation in the hippocampus of VPA-exposed rats. The results showed a defensive effect of environment-related lithium exposure doses on neurobehavioural deficits in the rat valproic acid model of autism, suggesting that it may be a potential drug for the treatment of autism.

Distinct Patterns of Gene Expression Changes in the Colon and Striatum of Young Mice Overexpressing Alpha-Synuclein Support Parkinson's Disease as a Multi-System Process

BACKGROUND

Evidence supports a role for the gut-brain axis in Parkinson's disease (PD). Mice overexpressing human wild type α- synuclein (Thy1-haSyn) exhibit slow colonic transit prior to motor deficits, mirroring prodromal constipation in PD. Identifying molecular changes in the gut could provide both biomarkers for early diagnosis and gut-targeted therapies to prevent progression.

OBJECTIVE

To identify early molecular changes in the gut-brain axis in Thy1-haSyn mice through gene expression profiling.

METHODS

Gene expression profiling was performed on gut (colon) and brain (striatal) tissue from Thy1-haSyn and wild-type (WT) mice aged 1 and 3 months using 3' RNA sequencing. Analysis included differential expression, gene set enrichment and weighted gene co-expression network analysis (WGCNA).

RESULTS

At one month, differential expression (Thy1-haSyn vs. WT) of mitochondrial genes and pathways related to PD was discordant between gut and brain, with negative enrichment in brain (enriched in WT) but positive enrichment in gut. Linear regression of WGCNA modules showed partial independence of gut and brain gene expression changes. Thy1-haSyn-associated WGCNA modules in the gut were enriched for PD risk genes and PD-relevant pathways including inflammation, autophagy, and oxidative stress. Changes in gene expression were modest at 3 months.

CONCLUSIONS

Overexpression of haSyn acutely disrupts gene expression in the colon. While changes in colon gene expression are highly related to known PD-relevant mechanisms, they are distinct from brain changes, and in some cases, opposite in direction. These findings are in line with the emerging view of PD as a multi-system disease.

In Search of Biomarkers to Guide Interventions in Autism Spectrum Disorder: A Systematic Review

OBJECTIVE

The aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials.

METHODS

A systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included.

RESULTS

A total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis."

CONCLUSIONS

There is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.

Gene Alterations Induced by Glutamine (Q) Encoding CAG Repeats Associated with Neurodegeneration

Several studies have been reported linking the role of polyglutamine (polyQ) disease-associated proteins with altered gene regulation induced by an unstable trinucleotide (CAG) repeat. Owing to their dynamic nature of expansion, these DNA repeats form secondary structures interfering with the normal cellular mechanisms like replication and transcription and, thereby, have become the underlying cause of numerous neurodegenerative disorders involving mental retardation and/or muscular or neuronal degeneration. Despite the widespread expression of the disease-causing protein, specific subsets of neurons are susceptible to specific patterns of inheritance and clinical symptoms. Although this cell-type selectivity is still elusive and less understood, it has been found that aberrant transcriptional regulation is one of the primary causes of polyQ diseases where the functions of histone-modifying complexes are disrupted. Besides, epigenetic modifications play a critical role in the pathogenesis of these diseases. In this chapter, we will be delving into how these polyQ repeats induce the self-assembly and aggregation of altered carrier proteins based on gene alterations, causing neuronal toxicity and cellular deaths. Besides, genomic instability in CAG repeats due to altered chromatin-related enzymes will be highlighted, along with epigenetic changes present in many polyQ disorders. Understanding the underlying molecular mechanisms in the root cause of these disorders will culminate in identifying therapeutic approaches for the treatment of these neurodegenerative disorders.

Neurodevelopmental disorders: 2023 update

Several advances in the field of neurodevelopmental diseases (NDDs) have been reported by 2022. Of course, NDDs comprise a diverse group of disorders, most of which with different aetiologies. However, owing to the development and consolidation of technological approaches, such as proteomics and RNA-sequencing, and to the improvement of brain organoids along with the introduction of artificial intelligence (AI) for biodata analysis, in 2022 new aetiological mechanisms for some NDDs have been proposed. Here, we present hints of some of these findings. For instance, centrioles regulate neuronal migration and could be behind the aetiology of periventricular heterotopia; also, the accumulation of misfolded proteins could explain the neurological effects in COVID-19 patients; and, autism spectrum disorders (ASD) could be the expression of altered cortical arealization. We also cover other interesting aspects as the description of a new NDD characterized by deregulation of genes involved in stress granule (SG) assemblies, or the description of a newly discovered neural progenitor that explains the different phenotypes of tumours and cortical tubers in tuberous sclerosis complex (TSC) disease; and how it is possible to decipher the aetiology of sudden unexplained death in childhood (SUDC) or improve the diagnosis of cortical malformations using formalin-fixed paraffin-embedded samples.

Persistent Inflammation Initiated by TORCH Infections and Dysbiotic Microbiome in Autism Spectrum Disorders: A Prospect for Future Interventions

Autism spectrum disorders (ASD) are a range of neurodevelopmental conditions that are clinically present early in childhood with the symptoms of social withdrawal and repetitive behavior. Despite an extensive research on ASD, no commonly accepted theory on the disease etiology exists. Hence, we reviewed several scientific publications, including reviews, preclinical and clinical investigations, and published hypotheses to analyze various opinions on the nature and cause of the disorder. Many studies suggest that infections and inflammation during pregnancy play a significant role in genetic and epigenetic changes in the developing fetus, resulting in an autistic phenotype in a child. Still, there is a lack of comprehensive literature about the multitude of autism inducing factors. Therefore, this article reviews and discusses available scientific evidence on the roles of viral, bacterial, fungal, and parasitic infections, overactivation of the immune system, and intestinal microflora in the pathogenesis and clinical manifestation of ASD. The overview of the scientific publications, including our own studies, suggests that TORCH infections, imbalanced microbiome, and persistent inflammation are significantly associated with the disruption of the social domain in ASD children. The ASD-related changes begin prenatally as maternal-to-fetal immune activation triggered by infection. It results in continuous low-grade inflammation and oxidative stress in a fetus, causing germline and somatic genetic changes in the developing brain and the establishment of the dysregulated immune system. These changes and dysregulations result in central and peripheral nervous systems dysfunctions as well as other comorbid conditions found in autistic children.

High-throughput functional annotation of natural products by integrated activity profiling

Determining mechanism of action (MOA) is one of the biggest challenges in natural products discovery. Here, we report a comprehensive platform that uses Similarity Network Fusion (SNF) to improve MOA predictions by integrating data from the cytological profiling high-content imaging platform and the gene expression platform Functional Signature Ontology, and pairs these data with untargeted metabolomics analysis for de novo bioactive compound discovery. The predictive value of the integrative approach was assessed using a library of target-annotated small molecules as benchmarks. Using Kolmogorov-Smirnov (KS) tests to compare in-class to out-of-class similarity, we found that SNF retains the ability to identify significant in-class similarity across a diverse set of target classes, and could find target classes not detectable in either platform alone. This confirmed that integration of expression-based and image-based phenotypes can accurately report on MOA. Furthermore, we integrated untargeted metabolomics of complex natural product fractions with the SNF network to map biological signatures to specific metabolites. Three examples are presented where SNF coupled with metabolomics was used to directly functionally characterize natural products and accelerate identification of bioactive metabolites, including the discovery of the azoxy-containing biaryl compounds parkamycins A and B. Our results support SNF integration of multiple phenotypic screening approaches along with untargeted metabolomics as a powerful approach for advancing natural products drug discovery.

Challenges and opportunities for precision medicine in neurodevelopmental disorders

Neurodevelopmental Disorders (NDDs) encompass a broad spectrum of disorders, linked because of their origins in brain developmental processes, including diverse conditions across the age span, including autism spectrum disorders (ASD) and schizophrenia (SCZ). Clinical treatment of these disorders has traditionally focused on symptom management, as the severity of developmental disruption varies widely and the precise molecular mechanisms, timing, and progression of these disorders is usually not known. Several hundred genes have been identified as major risk factors for ASD and SCZ, which creates new potential therapeutic avenues, and there is strong evidence that these genes converge upon key molecular pathways, pointing to opportunities for precision medicine. In this review, we focus on forms of ASD and SCZ with known genetic etiologies and discuss advances in research technologies that enable a more systemic understanding of disease progression. We highlight recent advances in targeted clinical treatment and discuss ongoing preclinical efforts as well as new initiatives aimed at developing scalable platforms for NDD precision medicine.

Future Prospects for Epigenetics in Autism Spectrum Disorder

Despite decades of investigation into the genetics of autism spectrum disorder (ASD), a current consensus in the field persists that ASD risk is too heterogeneous to be diagnosed by a single set of genetic variants. As such, ASD research has broadened to include assessment of other molecular biomarkers implicated in the condition that may be reflective of environmental exposures or gene by environment interactions. Epigenetic variance, and specifically differential DNA methylation, have emerged as areas of particularly high interest to ASD, as the epigenetic markers from specific chromatin loci collectively can reflect influences of multiple genetic and environmental factors and can also result in differential gene expression patterns. This review examines recent studies of the ASD epigenome, detailing common gene pathways found to be differentially methylated in people with ASD, and considers how these discoveries may inform our understanding of ASD etiology. We also consider future applications of epigenetics in ASD research and clinical practice, focusing on substratification, biomarker development, and experimental preclinical models of ASD that test causality. In combination with other -omics approaches, epigenomics allows an improved conceptualization of the multifactorial nature of ASD, and opens future lines of inquiry for both basic research and clinical practice.

Broad transcriptomic dysregulation occurs across the cerebral cortex in ASD

Neuropsychiatric disorders classically lack defining brain pathologies, but recent work has demonstrated dysregulation at the molecular level, characterized by transcriptomic and epigenetic alterations1-3. In autism spectrum disorder (ASD), this molecular pathology involves the upregulation of microglial, astrocyte and neural-immune genes, the downregulation of synaptic genes, and attenuation of gene-expression gradients in cortex1,2,4-6. However, whether these changes are limited to cortical association regions or are more widespread remains unknown. To address this issue, we performed RNA-sequencing analysis of 725 brain samples spanning 11 cortical areas from 112 post-mortem samples from individuals with ASD and neurotypical controls. We find widespread transcriptomic changes across the cortex in ASD, exhibiting an anterior-to-posterior gradient, with the greatest differences in primary visual cortex, coincident with an attenuation of the typical transcriptomic differences between cortical regions. Single-nucleus RNA-sequencing and methylation profiling demonstrate that this robust molecular signature reflects changes in cell-type-specific gene expression, particularly affecting excitatory neurons and glia. Both rare and common ASD-associated genetic variation converge within a downregulated co-expression module involving synaptic signalling, and common variation alone is enriched within a module of upregulated protein chaperone genes. These results highlight widespread molecular changes across the cerebral cortex in ASD, extending beyond association cortex to broadly involve primary sensory regions.

The DNA Methylation in Neurological Diseases

DNA methylation is critical for the normal development and functioning of the human brain, such as the proliferation and differentiation of neural stem cells, synaptic plasticity, neuronal reparation, learning, and memory. Despite the physical stability of DNA and methylated DNA compared to other epigenetic modifications, some DNA methylation-based biomarkers have translated into clinical practice. Increasing reports indicate a strong association between DNA methylation profiles and various clinical outcomes in neurological diseases, making DNA methylation profiles valuable as novel clinical markers. In this review, we aim to discuss the latest evidence concerning DNA methylation alterations in the development of neurodegenerative, neurodevelopmental, and neuropsychiatric diseases. We also highlighted the relationship of DNA methylation alterations with the disease progression and outcome in many neurological diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, frontotemporal dementia, and autism.

Multiplexed functional genomic assays to decipher the noncoding genome

Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.

Cerebral Organoids as an Experimental Platform for Human Neurogenomics

The cerebral cortex forms early in development according to a series of heritable neurodevelopmental instructions. Despite deep evolutionary conservation of the cerebral cortex and its foundational six-layered architecture, significant variations in cortical size and folding can be found across mammals, including a disproportionate expansion of the prefrontal cortex in humans. Yet our mechanistic understanding of neurodevelopmental processes is derived overwhelmingly from rodent models, which fail to capture many human-enriched features of cortical development. With the advent of pluripotent stem cells and technologies for differentiating three-dimensional cultures of neural tissue in vitro, cerebral organoids have emerged as an experimental platform that recapitulates several hallmarks of human brain development. In this review, we discuss the merits and limitations of cerebral organoids as experimental models of the developing human brain. We highlight innovations in technology development that seek to increase its fidelity to brain development in vivo and discuss recent efforts to use cerebral organoids to study regeneration and brain evolution as well as to develop neurological and neuropsychiatric disease models.

Tissue-wide cell-specific proteogenomic modeling reveals novel candidate risk genes in autism spectrum disorders

Autism spectrum disorders (ASD) are a set of complex neurodevelopmental diseases characterized with repetitive behavioral patterns and communication disabilities. Using a systems biology method called MAPSD (Markov Affinity-based Proteogenomic Signal Diffusion) for joint modeling of proteome dynamics and a wide array of omics datasets, we identified a list of candidate ASD risk genes. Leveraging the collected biological signals as well as a large-scale protein-protein interaction network adjusted based on single cell resolution proteome properties in four brain regions, we observed an agreement between the known and the newly identified candidate genes that are spatially enriched in neuronal cells within cerebral cortex at the protein level. Moreover, we created a detailed subcellular localization enrichment map of the known and the identified genes across 32 micro-domains and showed that neuronal cells and neuropils share the largest fraction of signal enrichment in cerebral cortex. Notably, we showed that the identified genes are among the transcriptional biomarkers of inhibitory and excitatory neurons in human frontal cortex. Intersecting the identified genes with a single cell RNA-seq data on ASD brains further evidenced that 20 candidate genes, including GRIK1, EMX2, STXBP6, and KCNJ3 are disrupted in distinct cell-types. Moreover, we showed that ASD risk genes are predominantly distributed in certain human interactome modules, and that the identified genes may act as the regulator for some of the known ASD loci. In summary, our study demonstrated how tissue-wide cell-specific proteogenomic modeling can reveal candidate genes for brain disorders that can be supported by convergent lines of evidence.

Rare variants and the oligogenic architecture of autism

Most large-scale genetic studies of autism have focused on the discovery of genes by proving an enrichment of de novo mutations (DNMs) in autism probands or characterizing polygenic risk based on the association of common variants. We present evidence in support of an oligogenic model where two or more ultrarare mutations of more modest effect are preferentially transmitted to children with autism. Such private gene-disruptive mutations are enriched in families where there are multiple affected individuals, emerged two or three generations ago, and map to genes not previously associated with autism. Although no single gene has reached statistical significance, this class of variation should be considered along with genetic and nongenetic factors to better explain the etiology of this complex trait.

The association between ST8SIA2 gene and behavioral phenotypes in children with autism spectrum disorder

Objective

ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 2 (ST8SIA2) encodes a type II membrane protein that is thought to catalyze the transfer of sialic acid (SA) from CMP-SA to N-linked oligosaccharides and glycoproteins. Some population and animal studies have indicated an association between the ST8SIA2 gene and autism spectrum disorder (ASD). However, there is limited information on the correlation between ST8SIA2 and autistic behavioral symptoms.

Methods

In this study, 69 ASD and 76 normal control children who were age- and sex-matched were recruited. ST8SIA2 expression and methylation levels were measured by reverse transcription quantitative real-time PCR and pyrosequencing, respectively, and the behavioral phenotypes of ASD children were assessed.

Results

The ASD group had lower ST8SIA2 gene expression levels than the control group [t(0.05/2,143) = 2.582, p = 0.011]. Moreover, ST8SIA2 expression levels were positively correlated with daily life skills (rs = 0.381, p = 0.008) and negatively associated with stereotyped behaviors in the ASD group (rs = -0.510, p = 0.004). The methylation levels of the Chr. 15: 92984625 and Chr. 15: 92998561 sites of the ST8SIA2 gene in ASD children were higher than those of controls. The Chr. 15: 92984625 site was positively correlated with the stereotyped behaviors of ASD children (rs = 0.41, p = 0.039).

Conclusion

This study provides a scientific basis to elucidate the relationship between the ST8SIA2 gene and behavioral phenotypes of ASD.

Can epigenetics shine a light on the biological pathways underlying major mental disorders?

A significant proportion of the global burden of disease can be attributed to mental illness. Despite important advances in identifying risk factors for mental health conditions, the biological processing underlying causal pathways to disease onset remain poorly understood. This represents a limitation to implement effective prevention and the development of novel pharmacological treatments. Epigenetic mechanisms have emerged as mediators of environmental and genetic risk factors which might play a role in disease onset, including childhood adversity (CA) and cannabis use (CU). Particularly, human research exploring DNA methylation has provided new and promising insights into the role of biological pathways implicated in the aetio-pathogenesis of psychiatric conditions, including: monoaminergic (Serotonin and Dopamine), GABAergic, glutamatergic, neurogenesis, inflammatory and immune response and oxidative stress. While these epigenetic changes have been often studied as disease-specific, similarly to the investigation of environmental risk factors, they are often transdiagnostic. Therefore, we aim to review the existing literature on DNA methylation from human studies of psychiatric diseases (i) to identify epigenetic modifications mapping onto biological pathways either transdiagnostically or specifically related to psychiatric diseases such as Eating Disorders, Post-traumatic Stress Disorder, Bipolar and Psychotic Disorder, Depression, Autism Spectrum Disorder and Anxiety Disorder, and (ii) to investigate a convergence between some of these epigenetic modifications and the exposure to known risk factors for psychiatric disorders such as CA and CU, as well as to other epigenetic confounders in psychiatry research.

Integrative analysis prioritised oxytocin-related biomarkers associated with the aetiology of autism spectrum disorder

Background

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with high phenotypic and genetic heterogeneity. The common variants of specific oxytocin-related genes (OTRGs), particularly OXTR, are associated with the aetiology of ASD. The contribution of rare genetic variations in OTRGs to ASD aetiology remains unclear.

Methods

We catalogued publicly available de novo mutations (DNMs) [from 6,511 patients with ASD and 3,391 controls], rare inherited variants (RIVs) [from 1,786 patients with ASD and 1,786 controls], and both de novo copy number variations (dnCNVs) and inherited CNVs (ihCNVs) [from 15,581 patients with ASD and 6,017 controls] in 963 curated OTRGs to explore their contribution to ASD pathology, respectively. Finally, a combined model was designed to prioritise the contribution of each gene to ASD aetiology by integrating DNMs and CNVs.

Findings

The rare genetic variations of OTRGs were significantly associated with ASD aetiology, in the order of dnCNVs > ihCNVs > DNMs. Furthermore, 172 OTRGs and their connected 286 ASD core genes were prioritised to positively contribute to ASD aetiology, including top-ranked MAPK3. Probands carrying rare disruptive variations in these genes were estimated to account for 10∼11% of all ASD probands.

Interpretation

Our findings suggest that rare disruptive variations in 172 OTRGs and their connected 286 ASD core genes are associated with ASD aetiology and may be potential biomarkers predicting the effects of oxytocin treatment.

Funding

Guangdong Key Project, National Natural Science Foundation of China, Key Laboratory of Clinical Laboratory Diagnosis and Translational Research of Zhejiang Province.

Epigenetics of Autism Spectrum Disorder: Histone Deacetylases

The etiology of autism spectrum disorder (ASD) remains unknown, but gene-environment interactions, mediated through epigenetic mechanisms, are thought to be a key contributing factor. Prenatal environmental factors have been shown to be associated with both increased risk of ASD and altered histone deacetylases (HDACs) or acetylation levels. The relationship between epigenetic changes and gene expression in ASD suggests that alterations in histone acetylation, which lead to changes in gene transcription, may play a key role in ASD. Alterations in the acetylome have been demonstrated for several genes in ASD, including genes involved in synaptic function, neuronal excitability, and immune responses, which are mechanisms previously implicated in ASD. We review preclinical and clinical studies that investigated HDACs and autism-associated behaviors and discuss risk genes for ASD that code for proteins associated with HDACs. HDACs are also implicated in neurodevelopmental disorders with a known genetic etiology, such as 15q11-q13 duplication and Phelan-McDermid syndrome, which share clinical features and diagnostic comorbidities (e.g., epilepsy, anxiety, and intellectual disability) with ASD. Furthermore, we highlight factors that affect the behavioral phenotype of acetylome changes, including sensitive developmental periods and brain region specificity in the context of epigenetic programming.

Bringing machine learning to research on intellectual and developmental disabilities: taking inspiration from neurological diseases

Intellectual and Developmental Disabilities (IDDs), such as Down syndrome, Fragile X syndrome, Rett syndrome, and autism spectrum disorder, usually manifest at birth or early childhood. IDDs are characterized by significant impairment in intellectual and adaptive functioning, and both genetic and environmental factors underpin IDD biology. Molecular and genetic stratification of IDDs remain challenging mainly due to overlapping factors and comorbidity. Advances in high throughput sequencing, imaging, and tools to record behavioral data at scale have greatly enhanced our understanding of the molecular, cellular, structural, and environmental basis of some IDDs. Fueled by the "big data" revolution, artificial intelligence (AI) and machine learning (ML) technologies have brought a whole new paradigm shift in computational biology. Evidently, the ML-driven approach to clinical diagnoses has the potential to augment classical methods that use symptoms and external observations, hoping to push the personalized treatment plan forward. Therefore, integrative analyses and applications of ML technology have a direct bearing on discoveries in IDDs. The application of ML to IDDs can potentially improve screening and early diagnosis, advance our understanding of the complexity of comorbidity, and accelerate the identification of biomarkers for clinical research and drug development. For more than five decades, the IDDRC network has supported a nexus of investigators at centers across the USA, all striving to understand the interplay between various factors underlying IDDs. In this review, we introduced fast-increasing multi-modal data types, highlighted example studies that employed ML technologies to illuminate factors and biological mechanisms underlying IDDs, as well as recent advances in ML technologies and their applications to IDDs and other neurological diseases. We discussed various molecular, clinical, and environmental data collection modes, including genetic, imaging, phenotypical, and behavioral data types, along with multiple repositories that store and share such data. Furthermore, we outlined some fundamental concepts of machine learning algorithms and presented our opinion on specific gaps that will need to be filled to accomplish, for example, reliable implementation of ML-based diagnosis technology in IDD clinics. We anticipate that this review will guide researchers to formulate AI and ML-based approaches to investigate IDDs and related conditions.